Storing a full candidate snapshot on every observation was the wrong call. The same node lists got copied thousands of times, about 22 GB on prod. Resolve endpoints live like path hops and drop the column.
The payload-breakdown and top-observers matviews stored a single 7-day
total per group, so the 24h/7d/30d selector did nothing: payload ignored
the window entirely (the store discarded `since`) and top-observers only
varied which rows cleared the last_heard cutoff, never the counts.
Bucket both views by hour over a 30-day horizon and sum the buckets in
range, mirroring mv_hourly_iata_stats. The stats endpoints now honour the
requested window while still reading a small precomputed table.
The trace list joined every trace packet to ~50M observations to apply
the IATA filter; the parallel hash join overran docker's 64MB /dev/shm
and the filtered list errored. Keep a small trace_iatas table at ingest
(like channel_iatas) and group packets by tag instead. Filtered stats
are now per tag rather than per matching packet.
The IATA filter ran a correlated EXISTS over packets/observations with
ILIKE, which skipped the iata index and took ~7s live. Keep a small
channel_iatas table at ingest (like node_iatas) and filter against it.
Also honor the iatas= param so multi-site regions stop getting the
global list. Filter now ages out with packet retention rather than
matching any retained packet.
Quiet sites probed hundreds of thousands of packets to fill a page.
Walk idx_observations_iata_heard per requested site and dedup instead.
Filtered lists now order by site-local recency; the cursor follows.
text[] from string_to_array can't match the CHAR(3) indexes and hides
the values from the planner. Handlers already have a slice; stop
joining to CSV in the store layer and pass a typed array everywhere.
n30nex